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Physics-based lumped-parameter modeling of automotive canister fuel purge

机译:汽车罐燃油净化的基于物理的集总参数建模

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A physics-based canister fuel purge flowrate model based on fluid mechanics and thermodynamics principles is presented in this paper to improve the tailpipe emission control in automotive applications. The aim of the paper is to derive a lumped-parameter model for the canister that estimates the flowrate out of the canister purged into the intake manifold. The lumped parameters of the model, including canister capacitance and flow resistance are employed to obtain a first-order multi-input and single-output (MISO) dynamic model. The vacuum pressure in the intake manifold and the fuel tank pressure serve as inputs and the mass flowrate is considered as the model output. Gradient descent system identification method is used to estimate the model parameters based on experimental data collected at Ford Motor Company. The advantage of the model is that it does not require cumbersome integral or differential computational methods and is easy to implement for fueling control purposes. Hence, it allows direct implementation in the fueling control to compensate for the extra fuel benefiting the stoichiometric air/fuel regulation in the engine catalyst.
机译:本文提出了一种基于流体力学和热力学原理的基于物理的罐式燃料吹扫流量模型,以改善汽车应用中的排气管排放控制。本文的目的是为滤罐导出集总参数模型,以估算从滤罐吹入进气歧管的流量。该模型的集总参数(包括罐电容和流阻)用于获得一阶多输入和单输出(MISO)动态模型。进气歧管中的真空压力和燃油箱压力用作输入,质量流量被视为模型输出。梯度下降系统识别方法用于基于福特汽车公司收集的实验数据来估计模型参数。该模型的优点是它不需要繁琐的积分或微分计算方法,并且易于实现用于加油控制的目的。因此,其允许直接在加油控制中实施以补偿有益于发动机催化剂中的化学计量空气/燃料调节的额外燃料。

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